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Record W4408813027 · doi:10.3390/jcm14072244

Lactate and pH as Independent Biomarkers for Prognosticating Meaningful Post-out-of-Hospital Cardiac Arrest Outcomes: A Systematic Review and Meta-Analysis

2025· review· en· W4408813027 on OpenAlexaboutno aff
Nalin M. Patel, Casey Carr, Charlotte Hopson, Charles W. Hwang

Bibliographic record

VenueJournal of Clinical Medicine · 2025
Typereview
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsnot available
FundersSociety of Transnational Academic Researchers Scholars NetworkUniversity of Florida
KeywordsMedicineMeta-analysisIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Background/Objectives: To systematically review the literature and to characterize the utility of lactate and pH for predicting survival and long-term neurological outcomes after out-of-hospital cardiac arrest (OHCA). Methods: PRISMA guidelines were followed. PubMed, Embase, Web of Science, Cochrane Central, and Academic Search Premier were searched for relevant studies. The population included adults with OHCA. Studies with majority in-hospital cardiac arrest (>50%) and studies predicting return of spontaneous circulation (ROSC) were excluded. Pairs of investigators reviewed the studies for relevance. Data were extracted and risk of bias was assessed using the Newcastle–Ottawa Scale. Meta-analyses were performed to characterize the relationship between lactate and pH with survival and neurological outcomes. Results: We included 21,120 patients over 49 studies. Most studies (78%) included OHCA only. Mean lactate of 7.24 (95%CI:6.05–8.44) was associated with favorable survival (n = 9155; 21 studies), while mean lactate of 7.15 (95%CI:6.37–7.93) was associated with favorable neurological outcome (n = 7534; 21 studies). Mean pH of 7.22 (95%CI:7.10–7.33) was associated with favorable survival (n = 4077; 7 studies), while a mean pH of 7.22 (95%CI:7.17–7.27) was associated with favorable neurological outcome (n = 6701; 13 studies). Poor outcomes were associated with lower pH and higher lactate values. Risk of bias was generally low to medium, while heterogeneity was high. Conclusions: A direct correlation exists between pH with survival and neurological outcome; the likelihood of favorable outcomes increases as pH increases. Conversely, an inverse relationship exists between lactate with survival and neurological outcome; higher lactate is associated with poorer outcomes. For lactate, the threshold for survival was more lenient than for favorable neurological outcome.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.045
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0220.043
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.101
GPT teacher head0.468
Teacher spread0.367 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2025
Admission routes1
Has abstractyes

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